Luc De Raedt

ORCID

Publication Activity (10 Years)

Years Active: 1988-2024
Publications (10 Years): 127

Top Venues

Publications

Gabriele Venturato, Vincent Derkinderen, Pedro Zuidberg Dos Martires, Luc De Raedt
Inference and Learning in Dynamic Decision Networks Using Knowledge Compilation. AAAI (2024)
Giuseppe Marra, Sebastijan Dumancic, Robin Manhaeve, Luc De Raedt
From statistical relational to neurosymbolic artificial intelligence: A survey. Artif. Intell. 328 (2024)
Adem Kikaj, Giuseppe Marra, Luc De Raedt
Subgraph Mining for Graph Neural Networks. IDA (1) (2024)
Vincent Derkinderen, Robin Manhaeve, Pedro Zuidberg Dos Martires, Luc De Raedt
Semirings for Probabilistic and Neuro-Symbolic Logic Programming. CoRR (2024)
Savitha Sam Abraham, Marjan Alirezaie, Luc De Raedt
CLEVR-POC: Reasoning-Intensive Visual Question Answering in Partially Observable Environments. CoRR (2024)
Vincent Derkinderen, Robin Manhaeve, Pedro Zuidberg Dos Martires, Luc De Raedt
Semirings for probabilistic and neuro-symbolic logic programming. Int. J. Approx. Reason. 171 (2024)
Victor Verreet, Luc De Raedt, Jessa Bekker
Modeling PU learning using probabilistic logic programming. Mach. Learn. 113 (3) (2024)
Jaron Maene, Vincent Derkinderen, Luc De Raedt
On the Hardness of Probabilistic Neurosymbolic Learning. CoRR (2024)
Rishi Hazra, Pedro Zuidberg Dos Martires, Luc De Raedt
SayCanPay: Heuristic Planning with Large Language Models Using Learnable Domain Knowledge. AAAI (2024)
Savitha Sam Abraham, Marjan Alirezaie, Luc De Raedt
CLEVR-POC: Reasoning-Intensive Visual Question Answering in Partially Observable Environments. LREC/COLING (2024)
Pedro Zuidberg Dos Martires, Luc De Raedt, Angelika Kimmig
Declarative Probabilistic Logic Programming in Discrete-Continuous Domains. CoRR (2023)
Rishi Hazra, Luc De Raedt
Deep Explainable Relational Reinforcement Learning: A Neuro-Symbolic Approach. CoRR (2023)
Maaike Van Roy, Pieter Robberechts, Wen-Chi Yang, Luc De Raedt, Jesse Davis
A Markov Framework for Learning and Reasoning About Strategies in Professional Soccer. J. Artif. Intell. Res. 77 (2023)
Rishi Hazra, Luc De Raedt
Deep Explainable Relational Reinforcement Learning: A Neuro-Symbolic Approach. ECML/PKDD (4) (2023)
Nitesh Kumar, Ondrej Kuzelka, Luc De Raedt
First-Order Context-Specific Likelihood Weighting in Hybrid Probabilistic Logic Programs. J. Artif. Intell. Res. 77 (2023)
Rishi Hazra, Pedro Zuidberg Dos Martires, Luc De Raedt
SayCanPay: Heuristic Planning with Large Language Models using Learnable Domain Knowledge. CoRR (2023)
Lennert De Smet, Pedro Zuidberg Dos Martires, Robin Manhaeve, Giuseppe Marra, Angelika Kimmig, Luc De Raedt
Neural Probabilistic Logic Programming in Discrete-Continuous Domains. CoRR (2023)
Jaron Maene, Luc De Raedt
Soft-Unification in Deep Probabilistic Logic. NeurIPS (2023)
Pietro Totis, Angelika Kimmig, Luc De Raedt
smProbLog: Stable Model Semantics in ProbLog for Probabilistic Argumentation. CoRR (2023)
Lennert De Smet, Pedro Zuidberg Dos Martires, Robin Manhaeve, Giuseppe Marra, Angelika Kimmig, Luc De Raedt
Neural probabilistic logic programming in discrete-continuous domains. UAI (2023)
Wen-Chi Yang, Giuseppe Marra, Gavin Rens, Luc De Raedt
Safe Reinforcement Learning via Probabilistic Logic Shields. NeSy (2023)
Pietro Totis, Luc De Raedt, Angelika Kimmig
. Theory Pract. Log. Program. 23 (6) (2023)
Thomas Eiter, Michael J. Maher, Enrico Pontelli, Luc De Raedt, Miroslaw Truszczynski
The Collection of Papers Celebrating the 20th Anniversary of TPLP, Part II. Theory Pract. Log. Program. 23 (1) (2023)
Wen-Chi Yang, Giuseppe Marra, Gavin Rens, Luc De Raedt
Safe Reinforcement Learning via Probabilistic Logic Shields. IJCAI (2023)
Wen-Chi Yang, Giuseppe Marra, Gavin Rens, Luc De Raedt
Safe Reinforcement Learning via Probabilistic Logic Shields. CoRR (2023)
Pietro Totis, Jesse Davis, Luc De Raedt, Angelika Kimmig
Lifted Reasoning for Combinatorial Counting. J. Artif. Intell. Res. 76 (2023)
Mohit Kumar, Samuel Kolb, Stefano Teso, Luc De Raedt
Learning MAX-SAT from contextual examples for combinatorial optimisation. Artif. Intell. 314 (2023)
Luc De Raedt, Ute Schmid, Johannes Langer
Approaches and Applications of Inductive Programming (Dagstuhl Seminar 23442). Dagstuhl Reports 13 (10) (2023)
Nitesh Kumar, Ondrej Kuzelka, Luc De Raedt
Learning Distributional Programs for Relational Autocompletion. Theory Pract. Log. Program. 22 (1) (2022)
Wen-Chi Yang, Arcchit Jain, Luc De Raedt, Wannes Meert
Parameter Learning in ProbLog with Annotated Disjunctions. IDA (2022)
Thomas Winters, Giuseppe Marra, Robin Manhaeve, Luc De Raedt
DeepStochLog: Neural Stochastic Logic Programming. AAAI (2022)
Tijl De Bie, Luc De Raedt, José Hernández-Orallo, Holger H. Hoos, Padhraic Smyth, Christopher K. I. Williams
Automating data science. Commun. ACM 65 (3) (2022)
Thomas Eiter, Michael J. Maher, Enrico Pontelli, Luc De Raedt, Miroslaw Truszczynski
Introduction to the Collection of Papers Celebrating the 20th Anniversary of TPLP. Theory Pract. Log. Program. 22 (6) (2022)
Wen-Chi Yang, Jean-François Raskin, Luc De Raedt
Lifted model checking for relational MDPs. Mach. Learn. 111 (10) (2022)
Dries Van Daele, Bram Weytjens, Luc De Raedt, Kathleen Marchal
OMEN: network-based driver gene identification using mutual exclusivity. Bioinform. 38 (12) (2022)
Mohit Kumar, Samuel Kolb, Stefano Teso, Luc De Raedt
Learning MAX-SAT from Contextual Examples for Combinatorial Optimisation. CoRR (2022)
Gavin Rens, Wen-Chi Yang, Jean-François Raskin, Luc De Raedt
Learning Probabilistic Temporal Safety Properties from Examples in Relational Domains. CoRR (2022)
Nitesh Kumar, Ondrej Kuzelka, Luc De Raedt
First-Order Context-Specific Likelihood Weighting in Hybrid Probabilistic Logic Programs. CoRR (2022)
Victor Verreet, Vincent Derkinderen, Pedro Zuidberg Dos Martires, Luc De Raedt
Inference and Learning with Model Uncertainty in Probabilistic Logic Programs. AAAI (2022)
Thomas Winters, Giuseppe Marra, Robin Manhaeve, Luc De Raedt
DeepStochLog: Neural Stochastic Logic Programming. CoRR (2021)
Pietro Totis, Angelika Kimmig, Luc De Raedt
SMProbLog: Stable Model Semantics in ProbLog and its Applications in Argumentation. CoRR (2021)
Andrew Cropper, Luc De Raedt, Richard Evans, Ute Schmid
Approaches and Applications of Inductive Programming (Dagstuhl Seminar 21192). Dagstuhl Reports 11 (4) (2021)
Simon Vandevelde, Victor Verreet, Luc De Raedt, Joost Vennekens
A Table-Based Representation for Probabilistic Logic: Preliminary Results. CoRR (2021)
Tijl De Bie, Luc De Raedt, José Hernández-Orallo, Holger H. Hoos, Padhraic Smyth, Christopher K. I. Williams
Automating Data Science: Prospects and Challenges. CoRR (2021)
Gust Verbruggen, Elia Van Wolputte, Sebastijan Dumancic, Luc De Raedt
avatar - Automated Feature Wrangling for Machine Learning. IDA (2021)
Simon Suster, Pieter Fivez, Pietro Totis, Angelika Kimmig, Jesse Davis, Luc De Raedt, Walter Daelemans
Mapping probability word problems to executable representations. EMNLP (1) (2021)
Robin Manhaeve, Sebastijan Dumancic, Angelika Kimmig, Thomas Demeester, Luc De Raedt
Neural probabilistic logic programming in DeepProbLog. Artif. Intell. 298 (2021)
Robin Manhaeve, Giuseppe Marra, Luc De Raedt
Approximate Inference for Neural Probabilistic Logic Programming. KR (2021)
Giuseppe Marra, Sebastijan Dumancic, Robin Manhaeve, Luc De Raedt
From Statistical Relational to Neural Symbolic Artificial Intelligence: a Survey. CoRR (2021)
Dirko Coetsee, Steve Kroon, McElory Hoffmann, Luc De Raedt
SpLyCI: Integrating Spreadsheets by Recognising and Solving Layout Constraints. IDA (2021)
Mohit Kumar, Samuel Kolb, Clément Gautrais, Luc De Raedt
Democratizing Constraint Satisfaction Problems through Machine Learning. AAAI (2021)
Arcchit Jain, Clément Gautrais, Angelika Kimmig, Luc De Raedt
Learning CNF Theories Using MDL and Predicate Invention. IJCAI (2021)
Gillis Hermans, Thomas Winters, Luc De Raedt
Shape Inference and Grammar Induction for Example-Based Procedural Generation. ICCC (2021)
Gust Verbruggen, Lidia Contreras Ochando, Cèsar Ferri, José Hernández-Orallo, Luc De Raedt
Muppets: Multipurpose Table Segmentation. IDA (2021)
Gillis Hermans, Thomas Winters, Luc De Raedt
Shape Inference and Grammar Induction for Example-based Procedural Generation. CoRR (2021)
Maaike Van Roy, Pieter Robberechts, Wen-Chi Yang, Luc De Raedt, Jesse Davis
Leaving Goals on the Pitch: Evaluating Decision Making in Soccer. CoRR (2021)
Mohit Kumar, Samuel Kolb, Luc De Raedt, Stefano Teso
Learning Mixed-Integer Linear Programs from Contextual Examples. CoRR (2021)
Wen-Chi Yang, Jean-François Raskin, Luc De Raedt
Lifted Model Checking for Relational MDPs. CoRR (2021)
Samuel Kolb, Stefano Teso, Anton Dries, Luc De Raedt
Predictive spreadsheet autocompletion with constraints. Mach. Learn. 109 (2) (2020)
Vincent Derkinderen, Evert Heylen, Pedro Zuidberg Dos Martires, Samuel Kolb, Luc De Raedt
Ordering Variables for Weighted Model Integration. UAI (2020)
Mohit Kumar, Samuel Kolb, Stefano Teso, Luc De Raedt
Learning MAX-SAT from Contextual Examples for Combinatorial Optimisation. AAAI (2020)
Andreas Persson, Pedro Zuidberg Dos Martires, Luc De Raedt, Amy Loutfi
Semantic Relational Object Tracking. IEEE Trans. Cogn. Dev. Syst. 12 (1) (2020)
Pedro Zuidberg Dos Martires, Nitesh Kumar, Andreas Persson, Amy Loutfi, Luc De Raedt
Symbolic Learning and Reasoning With Noisy Data for Probabilistic Anchoring. Frontiers Robotics AI 7 (2020)
Thomas Winters, Luc De Raedt
Discovering Textual Structures: Generative Grammar Induction using Template Trees. ICCC (2020)
Thomas Winters, Luc De Raedt
Discovering Textual Structures: Generative Grammar Induction using Template Trees. CoRR (2020)
Luc De Raedt, Sebastijan Dumancic, Robin Manhaeve, Giuseppe Marra
From Statistical Relational to Neuro-Symbolic Artificial Intelligence. IJCAI (2020)
Clément Gautrais, Yann Dauxais, Samuel Kolb, Arcchit Jain, Mohit Kumar, Stefano Teso, Elia Van Wolputte, Gust Verbruggen, Luc De Raedt
VisualSynth: Democratizing Data Science in Spreadsheets. ECML/PKDD (5) (2020)
Clément Gautrais, Yann Dauxais, Stefano Teso, Samuel Kolb, Gust Verbruggen, Luc De Raedt
Human-Machine Collaboration for Democratizing Data Science. CoRR (2020)
Luc De Raedt, Sebastijan Dumancic, Robin Manhaeve, Giuseppe Marra
From Statistical Relational to Neuro-Symbolic Artificial Intelligence. CoRR (2020)
Pedro Zuidberg Dos Martires, Nitesh Kumar, Andreas Persson, Amy Loutfi, Luc De Raedt
Symbolic Learning and Reasoning with Noisy Data for Probabilistic Anchoring. CoRR (2020)
Nitesh Kumar, Ondrej Kuzelka, Luc De Raedt
Learning Distributional Programs for Relational Autocompletion. CoRR (2020)
Vincent Derkinderen, Luc De Raedt
Algebraic Circuits for Decision Theoretic Inference and Learning. ECAI (2020)
Vaishak Belle, Luc De Raedt
Semiring programming: A semantic framework for generalized sum product problems. Int. J. Approx. Reason. 126 (2020)
Andreas Persson, Pedro Zuidberg Dos Martires, Luc De Raedt, Amy Loutfi
ProbAnch: a Modular Probabilistic Anchoring Framework. IJCAI (2020)
Samuel Kolb, Pedro Zuidberg Dos Martires, Luc De Raedt
How to Exploit Structure while Solving Weighted Model Integration Problems. UAI (2019)
Robin Manhaeve, Sebastijan Dumancic, Angelika Kimmig, Thomas Demeester, Luc De Raedt
DeepProbLog: Neural Probabilistic Logic Programming. BNAIC/BENELEARN (2019)
Ozan Arkan Can, Pedro Zuidberg Dos Martires, Andreas Persson, Julian Gaal, Amy Loutfi, Luc De Raedt, Deniz Yuret, Alessandro Saffiotti
Learning from Implicit Information in Natural Language Instructions for Robotic Manipulations. CoRR (2019)
Laura Antanas, Plinio Moreno, Marion Neumann, Rui Pimentel de Figueiredo, Kristian Kersting, José Santos-Victor, Luc De Raedt
Semantic and geometric reasoning for robotic grasping: a probabilistic logic approach. Auton. Robots 43 (6) (2019)
Luc De Raedt, Richard Evans, Stephen H. Muggleton, Ute Schmid
Approaches and Applications of Inductive Programming (Dagstuhl Seminar 19202). Dagstuhl Reports 9 (5) (2019)
Robin Manhaeve, Sebastijan Dumancic, Angelika Kimmig, Thomas Demeester, Luc De Raedt
DeepProbLog: Neural Probabilistic Logic Programming. CoRR (2019)
Luc De Raedt, Robin Manhaeve, Sebastijan Dumancic, Thomas Demeester, Angelika Kimmig
Neuro-Symbolic = Neural + Logical + Probabilistic. NeSy@IJCAI (2019)
Andreas Persson, Pedro Zuidberg Dos Martires, Amy Loutfi, Luc De Raedt
Semantic Relational Object Tracking. CoRR (2019)
Mohit Kumar, Stefano Teso, Patrick De Causmaecker, Luc De Raedt
Automating Personnel Rostering by Learning Constraints Using Tensors. ICTAI (2019)
Mohit Kumar, Stefano Teso, Luc De Raedt
Acquiring Integer Programs from Data. IJCAI (2019)
Pedro Zuidberg Dos Martires, Anton Dries, Luc De Raedt
Exact and Approximate Weighted Model Integration with Probability Density Functions Using Knowledge Compilation. AAAI (2019)
Arcchit Jain, Tal Friedman, Ondrej Kuzelka, Guy Van den Broeck, Luc De Raedt
Scalable Rule Learning in Probabilistic Knowledge Bases. AKBC (2019)
Samuel Kolb, Paolo Morettin, Pedro Zuidberg Dos Martires, Francesco Sommavilla, Andrea Passerini, Roberto Sebastiani, Luc De Raedt
The pywmi Framework and Toolbox for Probabilistic Inference using Weighted Model Integration. IJCAI (2019)
Yann Dauxais, Clément Gautrais, Anton Dries, Arcchit Jain, Samuel Kolb, Mohit Kumar, Stefano Teso, Elia Van Wolputte, Gust Verbruggen, Luc De Raedt
SynthLog: A Language for Synthesising Inductive Data Models (Extended Abstract). PKDD/ECML Workshops (1) (2019)
Luc De Raedt, Andrea Passerini, Stefano Teso
Learning Constraints From Examples. AAAI (2018)
Robin Manhaeve, Sebastijan Dumancic, Angelika Kimmig, Thomas Demeester, Luc De Raedt
DeepProbLog: Neural Probabilistic Logic Programming. CoRR (2018)
Gust Verbruggen, Luc De Raedt
Automatically Wrangling Spreadsheets into Machine Learning Data Formats. IDA (2018)
Bogdan Moldovan, Plinio Moreno, Davide Nitti, José Santos-Victor, Luc De Raedt
Relational affordances for multiple-object manipulation. Auton. Robots 42 (1) (2018)
Sergey Paramonov, Christian Bessiere, Anton Dries, Luc De Raedt
Sketched Answer Set Programming. ICTAI (2018)
Robin Manhaeve, Sebastijan Dumancic, Angelika Kimmig, Thomas Demeester, Luc De Raedt
DeepProbLog: Neural Probabilistic Logic Programming. NeurIPS (2018)
Samuel Kolb, Stefano Teso, Andrea Passerini, Luc De Raedt
Learning SMT(LRA) Constraints using SMT Solvers. IJCAI (2018)
Pedro Zuidberg Dos Martires, Anton Dries, Luc De Raedt
Knowledge Compilation with Continuous Random Variables and its Application in Hybrid Probabilistic Logic Programming. CoRR (2018)
Luc De Raedt, Hendrik Blockeel, Samuel Kolb, Stefano Teso, Gust Verbruggen
Elements of an Automatic Data Scientist. IDA (2018)
Mohit Kumar, Stefano Teso, Luc De Raedt
Automating Personnel Rostering by Learning Constraints Using Tensors. CoRR (2018)
Tijl De Bie, Luc De Raedt, Holger H. Hoos, Padhraic Smyth
Automating Data Science (Dagstuhl Seminar 18401). Dagstuhl Reports 8 (9) (2018)
José Oramas M., Luc De Raedt, Tinne Tuytelaars
Context-based object viewpoint estimation: A 2D relational approach. Comput. Vis. Image Underst. 160 (2017)

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Publication Activity (10 Years)

Top Topics

Top Venues

Luc De Raedt